Neural Network Components for Evolved Vision Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Kyle-Davidson:2018:CEEC,
-
author = "Cameron P. Kyle-Davidson and Adrian F. Clark",
-
booktitle = "2018 10th Computer Science and Electronic Engineering
(CEEC)",
-
title = "Neural Network Components for Evolved Vision Systems",
-
year = "2018",
-
pages = "202--207",
-
abstract = "This paper investigates the problem of integrating
convolutional neural networks with a computer vision
system that uses genetic programming to evolve image
classifiers. In previous cases, genetic algorithms have
been used to create and tune hyper-parameters of neural
networks. This paper presents a different method of
combining these two machine learning techniques, by
providing trained neural networks as components that
the genetic system may use. This approach makes such
networks available to the genetic algorithm during
training time, allowing the final evolved program to
potentially leverage the pattern recognition and image
classification abilities of various trained
convolutional neural networks to improve final
classification accuracy.",
-
keywords = "genetic algorithms, genetic programming",
-
DOI = "doi:10.1109/CEEC.2018.8674219",
-
month = sep,
-
notes = "Also known as \cite{8674219}",
- }
Genetic Programming entries for
Cameron P Kyle-Davidson
Adrian F Clark
Citations